PROJECT SUMMARY This proposal aims to continue the development of XNAT. XNAT is an imaging informatics platform designed to facilitate common management and productivity tasks for imaging and associated data. We will develop the next generation of XNAT technology to support the ongoing evolution of imaging research. Development will focus on modernizing and expanding the current system. In Aim 1, we will implement new web application infrastructure that includes a new archive file management system, a new event bus to manage cross-service orchestration and a new Javascript library to simplify user interface development. We will also implement new core services, including a Docker Container service, a dynamic scripting engine, and a global XNAT federation. In Aim 2, we will implement two innovative new capabilities that build on the services developed in Aim 1. The XNAT Publisher framework will streamline the process of data sharing by automating the creation and curation of data releases following best practices for data publication and stewardship. The XNAT Machine Learning framework will streamline the development and use of machine learning applications by integrating XNAT with the TensorFlow machine learning environment and implementing provenance and other monitoring features to help avoid the pitfalls that often plague machine learning efforts. For both Aim 1 and 2, all capabilities will be developed and evaluated in the context of real world scientific programs that are actively using the XNAT platform. In Aim 3, we will provide extensive support to the XNAT community, including training workshops, online documentation, discussion forums, and . These activities will be targeted at both XNAT users and developers.